69 lines
5.6 KiB
Markdown
69 lines
5.6 KiB
Markdown
# SolarLytics Requirements
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## Functional Requirements
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#### UML Diagram
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Main diagram describing the process of the complete project:
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<br> 
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The individual processing steps of the different datasets are shown here in more detail:
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<br> 
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## Non-functional Requirements
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### Must Have
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- **Compatibility**: The workflow must run on Windows and Mac OS. It should be easy to deploy and run in different environments.
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- **Documentation**: The documentation is for users and developers and must be available, including metadata, license information, a read-me file, and citation as well as contributing guidelines.
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- **Reproducibility**: The workflow must be reproducible.
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- **Testability**: The code must be well tested, with unit and integration tests in place.
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### Should Have
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- **Performance**: The workflow should able to process the datasets in a reasonable time.
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- **Maintainability**: The code should be well modularized and organized, following the standard template and PEP 8 guidelines. It should be refactured regularily.
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- **Easy-to-Use**: The workflow should provide a easy user experience
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### Could Have
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- **Accessibility**: The documentation could be translated to German.
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- **Presentation**: The workflow could have a visual support in the form of graphics.
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### Won't Have
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- **Add-ons**: Function for other countries.
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# Component Analysis
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| Abstract Workflow Node (Operation) | Input(s) | Output(s) |Implementation |
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|------------------------------------|-------------------------------------------|---------------------------------------|----------------------------------------------|
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|**photovoltaic data processing** | | |
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| load and clean photovoltaics data | original dataset (.csv) from destatis | dataframe (.csv) | CLI tool built on pandas
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| trim photovoltaic | dataframe (.csv) | dataframe(.csv) | CLI tool built on pandas
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| collapse columns photovoltaic | dataframe (.csv) | dataframe (.csv) | CLI tool built on pandas
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|**sunshine duration data processing** | | |
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| load sunshine duration data | DWD Website | sunshine duration data (.txt), one file for each month | CLI tool built on requests, os, bs4 and urllib
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| merge series | 12 sunshine duration datasets (.txt) | processed dataframe (.csv) | CLI tool built on pandas
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| collapse columns sunshine duration | dataframe (.csv) | dataframe (.csv) | CLI tool built on pandas
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| trim sunshine duration | dataframe (.csv) | dataframe (.csv) | CLI tool built on pandas
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|**solarparc data processing** | | |
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| load solarparc data and border data| OverpassAPI | .gpkg file (solarparc / border) | CLI http request over OverpassAPI, osmium, geopandas, shapely
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| calculate area | .gpkg file | .txt with report | CLI tool built on geopandas
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|**analysis** | | |
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| calculate theoretical energy | calculate area (.txt) & sunshine duration dataframe (.csv) | dataframe (.csv) | CLI tool built on pandas
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| collapse columns theoretical energy| dataframe (.csv) | dataframe (.csv) | CLI tool built on pandas
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| trim theoreticalenergy | dataframe (.csv) | energy differnce dataframe (.csv) | CLI tool built in pandas
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| calculate difference | theoritcal energy (.csv) & photovoltaic energy (.csv) | dataframe .csv | CLI tool built on pandas
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| plot energy difference | ernergy difference (.csv) | diagram over years (.png) | CLI tool built on matplotlib and pandas
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| plot yearly energy change | dataframe (.csv) | diagram over years (.png) | CLI tool built on matplotlib and pandas
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| plot solarparc map | .gpkg file (solarparc / border) | plot of germany (.png) | CLI tool built on matplotlib and geopandas
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| plot yearly change sunshine | dataframe (.csv) | diagram over years (.png) | CLI tool built on matplotlib and pandas
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| plot yearly change photovoltaic | dataframe (.csv) | diagram over years (.png) | CLI tool built on matplotlib and pandas
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| plot monthly change potovoltaic | dataframe (.csv) | diagram over months (.png) | CLI tool built on matplotlib and pandas
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| generate report | mutiple inputs (.txt, .png) | slides (.md) | built on markdown
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